The present invention relates in general to systems and techniques used to isolate a segmented image of a person or object from an ambient image of the area surrounding and including the person or object. In particular, the present invention relates to isolating a segmented image of an occupant from the ambient image of an occupant, where the ambient image of the occupant includes both the occupant and the area surrounding the occupant, so that the deployment of an airbag can be prevented or modified due to the characteristics of the segmented image of the occupant.
There are many situations in which it is desirable to isolate the segmented image of a “targeted” person or object from an ambient image which includes images ancillary to the “targeted” person or object. Airbag deployment systems can be one application of such a technology. Airbag deployment systems may need to make various deployment decisions that relate in one way or another to the image of an occupant. Airbag deployment systems can alter their behavior based on a wide variety of factors that ultimately relate in one way or another to the occupant. The type of occupant, the proximity of an occupant to the airbag, the velocity and acceleration of an occupant, the mass of the occupant, the amount of energy an airbag needs to absorb as a result of an impact between the airbag and the occupant, and other airbag deployment considerations may utilize characteristics of the occupant that can be obtained from a segmented image of the occupant.
There are significant obstacles in the existing art with regards to image segmentation techniques. First, prior art techniques do not function well in darker environments, such as when a car is being driven at night. Certain parts of a human occupant image can be rendered virtually invisible by darkness, depriving an airbag deployment system of accurate information. Second, such techniques do not compensate for varying degrees of darkness resulting from the fact that different parts of the occupant will be at different angles and distances from a sensor or light source. It is beneficial for different regions in the occupant image to be treated differently. Third, existing techniques do not maximize the intelligence that can be incorporated into the segmentation process when there is a specific type of segmented image. There are anatomical aspects of a human occupant that can be used to refine the raw segmented image of an occupant that is captured by a camera or other sensor. For example, the fact that all parts of a human being are connected, and the inherent nature of those connections, can enhance the ability of a segmentation process to determine which image pixels relate to the occupant, and which image pixels relate the area surrounding the occupant. The knowledge that the occupant is likely in some sort of seated position can also be used to apply more intelligence to a raw ambient image.